Cycle-Wise Process-Zone Model for Prediction of Delayed Hydride Cracking Initiation Under Flaw-Tip Hydride Ratcheting Conditions
Bibliographic record
Abstract
Flaws found during in-service inspection of Zr-2.5Nb pressure tubes in CANDU(1) reactors include fuel bundle scratches, debris fretting flaws, fuel bundle bearing pad fretting flaws and crevice corrosion flaws. These flaws are volumetric and blunt in nature. A key structural integrity concern with in-service blunt flaws is their susceptibility to delayed hydride cracking (DHC) initiation, particularly for debris fretting flaws under flaw-tip hydride ratcheting conditions. Hydride ratcheting conditions refer to situations when flaw-tip hydrides do not completely dissolve at normal operating temperature, and accumulation of flaw-tip hydrides occurs with each reactor heat-up/cool-down cycle. A significant number of in-service flaws are expected to be under hydride ratcheting conditions at late life of pressure tubes. DHC initiation evaluation procedures based on process-zone methodology for flaws under hydride ratcheting conditions are provided in CSA (Canadian Standards Association) N285.8-15. The process-zone model in CSA N285.8-15 predicts whether DHC initiation occurs or not for given flaw geometry and operating conditions, regardless of the number of reactor heat-up and cool-down cycles. There has been recent new development. Specifically, a cycle-wise process-zone model has been developed as an extension to the process-zone model in CSA N285.8-15. The cycle-wise process-zone model is able to predict whether DHC initiation occurs or not during a specific reactor heat-up and cool-down cycle under applied load. The development of the cycle-wise process-zone model was driven by the need to include flaw-tip stress relaxation due to creep in evaluation of DHC initiation. The technical basis for the development of the cycle-wise process-zone model for prediction of DHC initiation under flaw-tip hydride ratcheting conditions is described in this paper.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".